Sensitivity of subtropical wetland CH4 flux predictions to inundation parameterizations: A case study over the southeastern U.S.

Abstract:

Methane (CH₄) is an important greenhouse gas, and the predominant source of natural atmospheric CH₄ globally is its production in wetland soils. Wetlands and marshes in the southeastern U.S. comprise over 40 million acres of land and thus represent a significant component of the global climate system. CH₄ contributions from these and other subtropical systems remain difficult to quantify, however. Existing field measurements are lacking in both spatial and temporal coverage, inhibiting efforts to produce regional estimates through upscaling. Top-down constraints on emissions have been generated using satellite remote sensing retrievals of column CH4 (e.g., Frankenberg et al., 2005, 2008, Bergamaschi et al., 2007, 2013, Bloom et al., 2010, Wecht et al., 2014), but such approaches typically require preexisting emissions estimates to discern individual source contributions.

Land Surface Models (LSMs) have the potential to produce realistic results, but such predictions rely on accurate representations of sub-grid scale processes responsible for emissions. Since net fluxes are governed by complex interactions between local environmental and biogeochemical factors including water table position, soil temperature, soil substrate availability and vegetation type, reliable flux simulations depend not only upon how such processes are resolved but how skillfully the land surface state itself is predicted by a given model.

Here, we examine simulations using CLM4Me, a CH₄ biogeochemistry model run within CESM, and compare results to recently compiled flux estimations from satellite remote sensing data. We then examine how seasonal CH₄ flux simulations in CLM4Me are affected by alternative parameterizations of inundated land fraction. A global inundation dataset is calculated using DYPTOP, a newly-developed TOPMODEL implementation specifically designed to simulate the dynamics of wetland spatial distribution. We find evidence that DYPTOP may improve wetland CH₄ flux predictions over subtropical regions in CLM4.5, and propose a computationally efficient framework for fine-scale tuning of this scheme to more accurately represent the role of subtropical and temperate wetlands in global climate projections.